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We measured triadic closure in co-offending networks – i.e., the tendency of two individuals to co-offend if they share an accomplice – using a method that addresses the risk of overestimating clustering coefficients when using one-mode projections. We also assess the statistical significance of clustering coefficients using null models. The data relates to adult offenders (N = 274,689) connected to criminal investigations (N = 286,591) in Colombia. The observed coefficients range between 0.05 and 0.53 and are statistically significant, indicating that accomplices become sources of information about potential associates. They support the idea of preventing crime by targeting offenders' trustworthiness and disrupting information flows. • Clustering coefficients suggest that co-offending networks display triadic closure • Former accomplices become sources of information for new partners in crime • Assessing triadic closure in bipartite networks prevents overestimations • Null models assess the statistical significance of the clustering coefficients [ABSTRACT FROM AUTHOR]

Achieving sustainable development is regarded as a complex task and the SDGs have been designed to serve as guidelines for such goal. Since wetlands provide a wide range of environmental services to humanity, focusing on these ecosystems is crucial for achieving sustainable development in the countries in which the wetlands are located. The main objectives of this research were to: 1) Understand the SDG targets that should be prioritized in order to achieve sustainable development in specific iconic wetlands around the world, 2) identify feed backs and synergies across targets from a wetland perspective and 3) illustrate how wetland research can help achieve specific SDG targets. Data was collected on 36 wetlands across 5 continents and 17 countries by means of a questionnaire answered by 40 wetland researchers of the Global Ecohydrological Network (GWEN– www.gwennetwork.se) and designed by a selected group of these researchers during a meeting held in April in Santa Marta, Colombia in April 2018. Collected data were analyzed via both one-mode undirected and bipartite directed networks to answer the first two objectives. We found that of the 33 SDG targets that are wetland-related and that were previously selected for the study, four were considered a priority by at least 20 of the researchers: the Targets being 6.3 – "Improve water quality", 2.4 – "Ensure sustainable and resilient food production systems", 8.4 – "Sustainable Consumption and Production" and 12.2 – "Sustainable management of resources". Furthermore, targets 12.2, 6.3 and 2.4 resulted being the most influential by enabling and reinforcing the largest number of targets. However, target 2.4 counteracted and constrained the largest amount of targets, but at a much smaller scale than when compared to its positive influence. The network analysis resulted in the identification of four wetland groups with distinctive SDG-target bundles that researchers considered should be addressed as priority. We further illustrate for a particular iconic and degraded tropical wetland in Colombia, the Ciénaga Grande de Santa Marta, how hydrogeodesy (i.e., by Interferometric Synthetic Aperture Radar – InSAR) and ecohydrology studies can give valuable information to some of these priority SDG targets in the region. [ABSTRACT FROM AUTHOR]

In this paper, we analyse the bipartite Colombian firms-products network, throughout a period of five years, from 2010 to 2014. Our analysis depicts a strongly modular system, with several groups of firms specializing in the export of specific categories of products. These clusters have been detected by running the bipartite variant of the traditional modularity maximization, revealing a bi-modular structure. Interestingly, this finding is refined by applying a recently proposed algorithm for projecting bipartite networks on the layer of interest and, then, running the Louvain algorithm on the resulting monopartite representations. Important structural differences emerge upon comparing the Colombian firms-products network with the World Trade Web, in particular, the bipartite representation of the latter is not characterized by a similar block-structure, as the modularity maximization fails in revealing (bipartite) nodes clusters. This points out that economic systems behave differently at different scales: while countries tend to diversify their production—potentially exporting a large number of different products—firms specialize in exporting (substantially very limited) baskets of basically homogeneous products. [ABSTRACT FROM AUTHOR]